Overall, it was impressive to see so many experts in the field of database technology in one place. It seems the space is really picking up steam with cloud computing platforms, all the different efforts to merge the benefits of distributed data storage approaches like key-value stores and RDBMS and many others.

But what really was interesting from my perspective is that was a lot of different talks that mentioned implicitly or explicitly the processing graph structures and data-local analytics as an interesting approach to complex problem solving. Jeff Ullmann was talking about Map-Reduce extensions which included graph-like data structures. Susan B. Davidson gave a great talk on provenance and privacy, which involved a lot of workflow modeling that turns into graphs with access control on the workflow modules. I wonder if something like modeling ACLs in a graph could be of help here. Also, there was a lot of interest in processing of GIS and spatial problems like automatically discovering segments of movements in GPS traces, where at least some of the methods are a very interesting fit for graphs.

All in all – it is encouraging to see that there is a lot of research around the processing of complex data structures not only in scaling out but even coming up with ways to traverse graphs and express queries in ways that do not require the whole dataset to be touched. And the Property Graph Model is catching on, with a lot of databases (Neo4j, HBase, Redis, OrientDB etc) implementing support for it and thus making querying with Pipes (Dataflow) and Gremlin (Graph Query Language) an universal option to express rich queries on graphy data.

For this event, I prepared a graphy mindmap (click to open it), and had the chance to write on a real BLACKBOARD. Extremely cool and historic!